Enterprise portfolio analysis using finite state Markov decision process

ABSTRACT

Generating a transition plan for a computer resource portfolio, representing each resource as a state machine, by generating a transition plan, the transition plan having a set of acts for transitioning states of the resources, to move the computer resource portfolio from a present state, the present state based on an inventory of present computer capabilities, to a future state. The future state is identified based on a difference between a present state and an identified state meeting given performance requirements. The transition plan is optimized to maximize the sum value of the computer resource portfolio values added over the state sequence of the transition.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to enterprise portfoliomanagement and, more particularly, to the development of a set ofrecommendations in the form of a transition plan for the transition ofthe enterprise portfolio computer and software resources during eachphase of the planning horizon.

2. Background Description

Managing a portfolio of computer and software resources in asufficiently large business enterprise is a complicated and dauntingtask involving an analysis of a myriad of factors to include businesscapabilities, business value and business risk. Such factors are oftenboth competing and interlocked which makes it especially difficult toidentify an optimal portfolio transformation/evolution plan over a giventime duration. Portfolio transformation recommendations may be based on:business value and cost; adherence to functional requirements of theenterprise architecture; business risks; computer and software resourceslife cycles; and, interoperability and incompatibility amongst theportfolio computer and software resources. This effort is traditionallyperformed as a manual evaluation 901 as shown in FIG. 9. The businessfactors 911 which must be considered in order to develop a comprehensiveenterprise portfolio transition plan 912 include but are not limited tothe business values, business risks, enterprise architecture strategicobjectives, and co-dependencies and interoperability between portfoliomembers. This manual evaluation 901 can become an impossible task as thenumbers of portfolio members grows. Thus, the invention provides anautomated evaluation 902 for developing and optimizing an enterpriseportfolio of computer and software resources transition plan 912.

Presently, no deterministic techniques exist for automation ofenterprise portfolio transition management. Investment decisions intocomputer and software resources are currently not treated as formally asother business investments. This lack of formalism may lead to excessinvestment and computer and software resources that do not support thebusiness objectives or insufficient investment in computer and softwareresources, resulting in loss of business competitiveness.

SUMMARY OF THE INVENTION

A finite horizon discrete time Markov decision process (MDP) isdeveloped to model enterprise portfolio transformation. The MDP is amodel for executing sequential decision making. The key elements of anMDP are states, actions and rewards. A state is a quantity thatdescribes an essential characteristic of the problem. In this case thestate is the life cycle phase of all of the members in the portfolioconsidered collectively. In general, the state dynamics may be governedby a probability distribution and actions. The actions are made on atime set called a decision period. These periods are assumed fixed andknown a priori. The probability distribution specifies the chance of thestate moving to a different value during a decision period. The actionsinfluence the probability of the state transitions. The actions are thedecisions which are made that affect the state dynamics. A reward isassociated with an action and state transition. The decision maker wouldlike to select a sequence of actions which maximizes the sum of thereturns.

As the name suggests the model depends heavily on the Markov assumption.The Markov assumption is that the state evolution only depends on thepresent state and is independent of the past evolution of the state.Analogously, the Markov assumption requires that the rewards obtainedfor selecting a certain action in a given state only depend on thecurrent state and are independent of the prior history of the state.

In the context of enterprise portfolio selection, the state of theprocess is the vector representing the life cycle phase of each of themembers in the portfolio. For this invention, the members of theportfolio are the computer and software resources that meet a set ofrestrictions. The computer and software resources applicable to theinvention are those resources that have a definable business value, arelated business risk, are co-dependent with the other members of theportfolio, and are managed across a life cycle defined by states. Thestate of the MDP is a collection of individual state processes. Thestate is taken to be a discrete approximation of the continuouslifecycle of a resource. The state evolutions of the members in theportfolio are related via the actions.

For the purposes of this invention, the term computer and softwareresources is used to describe the members of the portfolio. However, itshould be understood that the members of the portfolio could be eithercomputer or software resources or both computer and software resources.For simplicity, the term computer and software resources or justresources is used throughout the description of the inventionembodiment.

An action for this model is a vector, called “resource actions,”representing the action taken on each of the resources in the portfolio.The collection of resource actions at a given time is called a portfolioaction.

When a resource action is taken, a reward is received. The reward for anaction in portfolio selection is the business value received by carryingout the action. This reward may be a cost benefit. Each of the computerand software resources in the portfolio has an action applied to it.Each resource contributes to the business value. The reward obtainedfrom a resource action is called a resource reward. The business rewardis the sum of the resource rewards. The resource rewards may be random.It is assumed that the resource rewards have a normal distribution. Thusthe business reward is the sum of normal random variables.

It is assumed that the resource rewards are correlated. This is to saythat the business value contribution of a computer and software resourcemay depend on the state of other computer and software resources in theportfolio. This is intended to model the interoperability andincompatibles that surely exist between resources. These synergies, ifleveraged, provide increased business value. This idea captures thenotion that the business value of the sum of the resources may begreater than the sum of business values of the individual computer andsoftware resources. The portfolio manager would like to take advantageof all such value fusion opportunities.

Existence of the enterprise architecture (EA) is assumed. Adherence of acomputer and software resources to the EA is known a priori. Thepreference to conform the portfolio to the EA is modeled as a rewardderived at the end of the planning horizon. If a computer and softwareresource is not EA compliant then the final reward or salvage functionplaces very low value on the resource being mature at the final time andplaces a high value on the resource being retired at the final time. Onthe other hand, if a computer and software resource is EA compliant thenthe final salvage function places high value on the retention of theresource in the portfolio.

It is assumed that the initial state of the portfolio is known. It isalso assumed that the salvage function for each of the computer andsoftware resources is known a priori. This is a part of an assessmentprocess which is assumed to be complete. Knowledge of the salvagefunction assumes that all current and potential computer and softwareresources in the portfolio have been evaluated for EA compliance.

The portfolio manager would like to maximize the business value whileinsuring that the chance of a large loss of business value is small.Risk adjusted business value is a measure of how much of the businessvalue is at risk given a portfolio action. It is assumed that the riskadjusted business value is additive. That is, total risk adjustedbusiness value (RABV) is the sum of the risk adjusted business valuereceived during each decision period in the planning horizon.

It is therefore an object of the present invention to provide a sequenceof portfolio actions which maximizes the discounted risk adjustedbusiness value and provide automatic generation of a transition plan forenterprise portfolio transition management within an enterprise whichreflects the optimized RABV for the enterprise.

It is a further object of the invention to define a relationship betweencomputer and software resources in the portfolio and financial aspectsof the business. The discounting factor measures how much the enterpriseprefers business value gains today over business value gains tomorrow.

It is another object of the invention to use this relationship toincorporate computer and software resource life cycle dynamics to definethe sequence of actions in terms of transitions across the life cyclestates.

An additional object of the invention is to consider interoperabilityand incompatibilities amongst computer and software resources within theportfolio to refine the business value and ensure adherence with theenterprise architecture.

According to the invention, there is provided a computer basedmethodology and system that evaluates current capabilities, called AS ISfeatures, and future requirements, called TO BE requirements, of thecomputer and software resources within an enterprise's portfolio. The ASIS features are obtained from a manual assessment of the existingcomputer and software resources. The TO BE requirements are developedfrom an analysis of the enterprise strategic goals to create the targetperformance capabilities of the computer and software resources withinthe portfolio. These future requirements may apply to existing resourcesor may include the incorporation of computer and software resources notyet part of the enterprise portfolio.

Upon analysis of the AS IS capabilities with the TO BE requirements, themethodology and related system will produce an optimized transitionplan. The transition plan is optimized by analyzing business risks andcosts relationships, interoperabilites and incompatibilities of membersof the portfolio, adherence to enterprise architecture, life cycle statetransitions probabilities, and other factors through a backwardinductive technique applied to a set of recursive equations that havebeen developed to model the myriad of business factors that effectportfolio transition management of computer and software resources.

The key insight of this solution method is that actions taken todayeffect the actions that can be taken tomorrow. Fewer choices for thefuture could mean smaller value. The portfolio manager should not onlyselect an action which maximizes the reward for today, but shouldoptimize a balance of today's reward with the expected rewards of thefuture.

For the purposes of this invention, the enterprise may be a singlecompany, a single department within a company (e.g., accounting, R&D,training, sales, etc.), a business concern that provides computingcapabilities for a number of customers, or numerous other entities thatmanage computer and software resources. The invention is concernedprimarily with the management and transition of IT applications withinan enterprise portfolio. However, the enterprise portfolio computer andsoftware resources, also referred to as portfolio members, may includehardware, software, firmware, and other assets that meet a set ofrestrictions. The invention restricts the automatic development of theenterprise portfolio transition plan to those computer and softwareresources that have a definable business value, a related business risk,are co-dependent with the other members of the portfolio, and aremanaged across a life cycle defined by states. That is, the computer andsoftware resources can exist in any one of several developmental oroperational states.

The enterprise portfolio computer and software resources may be anycollection of off-the-shelf, custom, turnkey or combination of softwarecapabilities within the enterprise as well as desktop, server, database,printer, facsimile, telecommunications, network and other computerhardware devices. Thus, the portfolio is a group of computer andsoftware resources that are currently available for transformation.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects and advantages will be betterunderstood from the following detailed description of a singleembodiment of the invention with reference to the drawings, in which:

FIG. 1 is a simplified block diagram that expresses the major elementsof the enterprise portfolio transition management of computer andsoftware resources.

FIG. 2 is a system level diagram showing an example of the members ofthe portfolio of computer and software resources that are to be managedby the enterprise portfolio transition management system.

FIG. 3 illustrates an example of a transition plan and the restrictionson members of the portfolio transition management system.

FIG. 4 illustrations the key elements of the computer-implementedportfolio transition management system.

FIG. 5 is an illustration of the life cycle of the members of theportfolio of computer and software resources and the related states.

FIG. 6 a shows the state transitions for a retain action.

FIG. 6 b shows the state transitions for a retire action.

FIG. 6 c shows the state transitions for a restructure action.

FIG. 7 is a flowchart describing the high level portfolio managementmethodology.

FIG. 8 is a flowchart of the optimization step.

FIG. 9 is an illustration of the current method of transition managementcompared with the subject inventions approach to transition management.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

Referring now to the drawings, and more particularly to FIG. 1, there isshown the portfolio transition management system 100 according to theinvention. The portfolio transition management system 100 analysesbusiness tactical and strategic values to produce a Transition Plan 104for the enterprise portfolio manager. A manual system, assessment 101 isperformed by the transition manager or the organization responsible fortransition management of computer and software resources within theenterprise to create an AS IS list of capabilities. This AS IS list ofcapabilities corresponds to the features and functions of each of theexisting computer and software resources currently in the enterpriseportfolio.

The transition manager or the organization responsible for transitionmanagement of computer and software resources within the enterprise alsoperforms a business value and risk assessment 102 to define thosethresholds and constraints that are used to refine the scope of thetransition planning. In this embodiment, the business value isdetermined as a composite of: Revenue growth, Cost reduction, Link tobusiness imperatives, Productivity enhancement, Competitive advantage,and Speed of benefit delivery. In another embodiment, a subset of thesefactors could be used or additional factors could be considered. Whilebusiness risk is a measure of business impact as a probability ofoccurrence over a lifetime and, in this embodiment, can be defined as acomposite of: Schedule Risks, Life cycle cost, Initial Costs,Feasibility risks, Reliability risks, Technical Risks (e.g., viruses,etc.), Management Risks, Security, and Technical obsolescence. Inanother embodiment, a subset of these factors could be used oradditional factors could be considered.

Furthermore, the computational requirement of the dynamic programmingalgorithm grows twice as fast in the number of states as the number ofactions. Thus the first approximation to the algorithm will prune thenumber of feasible states. An operational continuity constraint isintroduced. This constraint assumes that the enterprise desires toremain operational throughout the entire portfolio transition managementprocess. To reduce the computational effort needed to solve thisproblem, the following assumption can be made. It is assumed that anenterprise has a tolerance or threshold on the number of computer andsoftware resources it is willing to change over a given decision period.That is, the enterprise is capacitated in some way. Because ofconstraints on funding, man power and management complexity, anenterprise may want to limit the number of projects that it isundertaking in a given decision period.

Finally, the enterprise must provide strategic planning 103 inputs whichare analyzed by the portfolio transition management system 100 to derivethe TO BE future requirements. These requirements are defined by aSalvage Function {S_(j)(X_(n) ^(i),a_(n) ^(i))|0≦j≦K}, where theelements of the expression are defined to capture the functionalrequirements of an enterprise architecture. They represent the riskadjusted business value (RABV) associated with each life cycle phase ofa computer and software resource at the final time. The embodimentdescribed here speaks to computer and software resources that currentlyexist within the enterprise. However, it is easily understood by thoseskilled in the art that future requirements could include requirementsfor computer and software resources not currently included in theenterprise portfolio.

FIG. 2 provides an example of the computer and software resources thatmay be managed by the portfolio transition management system. Thecomputer and software resources may be interconnected through a network200. The network 200 is shown as a central network which interconnectscomputer and software resources. Those skilled in the art wouldunderstand that multiple local area networks, wide area networks, directconnections, and other connections could be implemented within theenterprise. Additionally, some of the computer and software resources tobe managed could operate as standalone computer resources 261.

The portfolio transition management system would accommodate managementof any number of different computer resources such as but not limited todesktop systems, laptop computers, servers, mainframe as well asancillary devices (e.g., printers, facsimiles, telephones, andtelecommunications equipment, etc.). In addition, the portfoliotransition management system would address the transition management ofcustomer enterprise solution applications (E.g., accounting, personnel,management, payroll, logistics and distribution, manufacturing, etc.) aswell as off-the-shelf applications.

The computer and software resources may include terminals (211, 212)which run desktop applications (e.g., Word™, Powerpoint™, LotusNotes™,customer solution applications, etc.) and/or act as front end terminalsfor mainframe and other types of computer systems (241, 242) and servers(221, 222). The computer systems (241, 242) and/or servers (221, 222)may run common system or server applications (e.g., DB2™, Websphere™,accounting applications, product distribution applications, networkmanagement applications, customer developed solutions, etc.). Thedatabases (251, 252) could be individual elements running databaseapplications (e.g., Access™, SQL™, Apache™, customer developedapplications, etc.) or could be configured within any of the othercomputer systems (241, 242) or servers (221, 222). Other computer andsoftware resources 231, such as telephones, cellular telephones,personal display devices (PDAs), printers, faxes, etc, may runapplications (e.g., e-mail, browser, address books, etc.) which may alsobe included in the portfolio transition management system.

FIG. 3 shows an example of the type of restrictions 301 that theportfolio transition management system 100 uses to select the computerand software resources for inclusion as members of the portfolio to betransitioned. These restrictions are used to distinguish the types ofenterprise assets for which a transition plan 302 is created by theportfolio transition management system. The restrictions include but arenot limited to the business risks, business values, decision periods,business costs, co-dependencies among computer and software resources,affinities, and that the resources are managed across a life cycledefined by state. Each member of the portfolio contributes to theoverall business value.

The actions are made on a time set called a decision period. Theseperiods are assumed fixed and known a priori. Thus, the decision periodmust be established and maintained as part of the transition data priorto the optimization of the transition plan 302.

The types of risks considered within the expression include: ScheduleRisks, Life cycle cost, Initial Costs, Feasibility risks, Reliabilityrisks, Technical Risks (viruses), Management Risks, Security, andTechnical obsolescence. These risks can be examined across various Areasof Risks within an enterprise such as: Organizational Change andManagement, Business, Data/Info, Technology, Strategic, Security,Privacy, and Project Resources as shown in Table 1. In anotherembodiment, a different set of areas of risk within an enterprise mayexist.

TABLE 1 Example of Risk Assessment Inputs Probability of Impact on Areaof Area Descrip- Occurrence Business Measure Risk Weight tion overlifetime (0-10) of Risk Security .2 Virus .3 2 .6 Business .6 Schedule.2 5 1 slip 2 months

FIG. 4 provides an illustration of the computers and network ofcomputers that could be configured to implement the portfolio transitionmanagement system 100. It is desirable that the status and other datarelative to the computer and software resources resides within thecomputers and networks of computers that communicate with the portfoliotransition management system through electronic connections such as thenetwork 200. In the event that the portfolio transition managementsystem is implemented in a standalone configuration 414, the status andother data would be entered manually by the transition manager through adata entry terminal 415. Although the data inputs would be enteredmanually, the processing of the data and the optimization of thetransition plan would be performed by the computing system. Due to thepotential for thousands of computer and software resources to betransitioned across an entire enterprise, the transition planning ofthese resources is performed using computers and networks of computersillustrated by FIG. 4.

The algorithms and other process capabilities could reside in the server412. The database 413 would be used to store the compiled data (AS IS,TO BE, transition planning data, and other data). The database 413 isshown as a separate element but could be storage within the server 412or standalone system 414 or computers and networked computers availablethrough the network 400. The transition plan could be distributedelectronically through the network 400. Additionally, a printingcapability 411 would be available to enable the transition plan to beprinted as a document.

FIG. 4 is a simplified diagram showing only one server 412, one dataentry terminal 415, one database 413 and one printing capability 411.However, it would be commonly understood by those skilled in the artthat although capable of running in a single server 412 or standalonesystem 414, the portfolio transition management system processing,storage, reporting and printing capabilities could be distributed acrossmultiple computers and networks of computers.

The life cycle of a computer and software resource is a major factor inhow much a computer and software resource contributes to the businessobjectives of the enterprise. When a computer and software resource isearly in its life cycle, e.g., undergoing development or deployment,then it may not contribute to business value at the same level as amature, steady state, computer and software resource. FIG. 5 provides adiscrete approximation of a computer and software resource life cycle.

The development phase 502 is when the computer and software resource isbeing created or being acquired. If the enterprise chooses an off theshelf product, then in the development phase the enterprise specifiesrequirements for the computer and software resource and createsselection criteria for purchasing the computer and software resource. Ifthe enterprise decides to make a custom computer and software resource,then the development phase includes the design and implementation of thecomputer and software resource.

The deployment phase 503 encompasses the installation of the computerand software resource and the time it takes to get the resourcefunctioning at the desired levels.

The steady state phase 504 represents the duration of time that thecomputer and software resource's functions are mature. The businessvalue of a computer and software resource in steady state is the highestcompared to the other life cycle phases.

In another embodiment, additional computer and software resourcelifecycle states may exist.

To model the computer and software resource life cycle, let {(X_(n)^(i)|n≧0} be a discrete time Markov chain representing the life cycle ofthe i-th resource in the portfolio. It is assumed that a resource's lifecycle phase is defined to be in one of the following 4 states: Dead 501,Develop 502, Deploy 503, or Steady State 504. The dead state 501 isincluded to model computer and software resources which are not in use.At time zero all of the candidate computer and software resources are inthe dead state 501. Let S_(i)={0,1,2,3} represent the state space of acomputer and software resource life cycle process. The state of thecomputer and software resource portfolio is expressed as the collectionof the life cycles of the individual computer and software resourcesthat compose the portfolio, X _(n)=(X_(n) ^(i), . . . , X_(n) ^(K)) Thestochastic process, { X _(n)|n≧0} is again a Markov chain and letS=S₁×S₂× . . . ×S_(K) be the state space of the computer and softwareresource portfolio.

At time n the portfolio manager must choose an action for each member ofthe portfolio. Let a_(n) ^(i) be the action applied to the i-th resourceat the time n. In this embodiment, the set of resource actions, A, is{Retain, Restructure, Retire}. In another embodiment, additional actionsmay exist. A portfolio action is defined to be the vector of allresource actions, ā_(n)=(a_(n) ^(i), . . . , a_(n) ^(K)) The space ofportfolio action is Ā=A₁=A₂× . . . ×A_(K). The portfolio transition planis the set of portfolio actions for the entire time horizon,ā=(ā_(n)|0≦n≦N).

FIG. 6 a shows the Retain action of state transitions. The retain action6 a keeps the computer and software in the current phase of its lifecycle until the beginning of the next decision period. That is, Develop611, Steady State 612 and Dead 613 do not transition to any other state.

FIG. 6 b illustrates the Retire action. The retire action sends acomputer and software resources to the dead state 623. The Develop 621and Steady State 622 will transition to Dead 623. The computer andsoftware is effectively removed from the portfolio.

FIG. 6 c illustrates the Restructure action. The restructure actionsends the computer and software resource back to the previous life cyclephase. That is, Dead 633 is transitioned back to Develop 631 whileDevelop 631 is transitioned to Steady State 632. Restructuring acomputer and software resource more than once does not add value to thecomputer and software resource, thus Steady State 632 is shown asremaining in the steady state phase. Restructuring a computer andsoftware resource simply causes a computer and software resource toperform up to its target capabilities (e.g., version updates, etc.).This assumption ensures that the rewards are Markovian. The discretetime assumption implies that the actions are recommended at knowninstances of time called decision periods. Each recommendation isexecuted completely during a decision period.

A portfolio action modifies the life cycle process of the computer andsoftware resource. In particular, a computer and software resourceaction performed on resource i, modifies the life cycle transitionprobabilities of only that resource. Given a resource action forresource i, the state transition of the i-th resource is independent ofthe resource actions performed on the other computer and softwareresources of the portfolio.

As previously mentioned, members of the portfolio are understood to bethe computer and software resources selected for the transitionmanagement. The terms member, member of the portfolio, computer andsoftware resources, and resources are used interchangeably throughoutthe description of the invention embodiment. In addition, for thepurposes of this invention, the term computer and software resources isused to describe the members of the portfolio. However, it should beunderstood that the members of the portfolio could be either computer orsoftware resources or both computer and software resources. Forsimplicity, the term computer and software resources or just resourcesis used throughout the description of the embodiment of the invention.

Referring now to FIG. 7, the portfolio transition management system canbe described by the flowchart shown. The system inputs data frombusiness plans 701 and from the enterprise architecture 702. The outputsinclude the AS IS 703 capabilities and the TO BE 704 requirements. Theportfolio transition manager may decide to develop a transition plan fora set of computer and software resources within the enterprise. Usingthe Business Plan 701 and Enterprise Architecture 702 as some of theinputs, the computer and software targeted for transition are select at710. The selection of these resources can be done manually by theportfolio transition manager and may include resources across theenterprise, computer and software resources only within a specific unitof the enterprise, only existing computer and software resources, onlynew computer and software resources, or any combination of theaforementioned or other groups.

Once the computer and software resources have been selected, anassessment is made of the existing capabilities of the target computerand software resources and the baseline of capabilities is establishedat 711. This baseline is expressed as AS IS 703 capabilities and can bestored on a database within the enterprise. The system then considersthe future requirements as expressed through the enterprise architecture702 and business plans 701 and defines future requirements for each ofthe selected computer and software resources at 712. The expression{S_(j)(X_(n) ^(i),a_(n) ^(i))|0≦j≦K} captures the functionalrequirements of the enterprise architecture in terms of TO BE 704requirements. The S_(j) represents the risk adjusted business valueassociated with each life cycle phase of a resource at the final time.The expression defines the TO BE 704 requirements in terms of the riskadjusted business value associated with each life cycle phase, theiterative state of a life cycle of the i-th resource [X_(n) ^(i)], andthe actions [a_(n) ^(i)]to be performed to achieve the life cycle stateover the planning period (0≦n≦N)., where the current decision period isn and the number of decision periods is N. These future requirements,expressed as TO BE 704, can also be stored on an enterprise database(251, 252), within the enterprise computer systems (241, 242), or withinany of the other computing elements discussed in FIG. 2.

The collection of the AS IS 703 capabilities and the TO BE 704requirements are then formatted with the specific targeted computer andsoftware resources and outputted as transition data 705 to be stored inan enterprise database (251, 252), within the other enterprise computersystems (241, 242) or within any of the other computing elementsdiscussed in FIG. 2. Once the transition data 705 has been created, thetransition planning is optimized at 713. This optimization is performedto maximize the business value for enterprise portfolio of computer andsoftware resources. FIG. 8 describes the optimization step 613 in moredetail.

Once the transition plan is optimized at 713 the data is outputted at614 as a physical report called the Transition Plan 706 or can bedistributed electronically across the enterprise through the network orcan be printed for manual distribution.

FIG. 8 provides a description of the optimization step 713 of FIG. 7.The transition data 705 (from FIG. 7) and the requirements data 801 (toinclude AS IS 703 and TO BE 704 of FIG. 6) is inputted and the statesand actions relationships for each computer and software resource areidentified at step 802. The relationship between states and actions forthe subject invention is defined by a dynamic programming algorithm.

The computational requirements of the dynamic programming algorithm growexponentially with the number of states of resources in the portfolio.For each time period the objective function is computed for each of the|S| states, during which a search over |A| actions is performed and foreach action the future cost is calculated for each of the |S| possiblestate transitions. The number of multiplications required for thedynamic programming algorithm is (N−1)|Ā|| S|². Thus, the life cyclestates and set of related actions for each resource are defined as |S|and |A|, respectively for step 802.

Modeling the enterprise portfolio become more accurate as the number ofresources in the portfolio grows large, where K represents the number ofresources. However dynamic programming becomes less efficient as thenumber of computations grow. The subject invention, therefore, appliesconstraints to the dynamic programming at step 803 to reduce the totalnumber of states and related sets of actions for which the maximumexpected RABV is calculated at step 804. The two constraints introducedat step 803 are operational continuity and project capacity. These twoconstraints lead to a reduction in the state space and the action spacepresented for maximizing the expected RABV.

The computational requirement of the dynamic programming algorithm growstwice as fast in the number of states as the number of actions. Thus thefirst approximation to the algorithm will prune the number of feasiblestates. To accomplish this, an operational continuity constraint isintroduced. This constraint assumes that the enterprise desires toremain operational throughout the entire portfolio management process.

The main capabilities of an enterprise should not be interrupted by theenterprise portfolio transition management process. Thus, the enterpriseshould be able to operate at all times throughout the enterpriseportfolio transition management process. The possible states of theportfolio are constrained by these capability requirements. This reducesthe set of possible states that the enterprise portfolio may attain.Each computer and software resource may support one or morecapabilities. Let C be the number of capabilities of an enterprise. TheS by C matrix, called [G^((i))] represents the capabilities support byresource i for each life cycle phase. The matrix G^((i)) is a zero orone matrix. The entry G_(kj) ^((i)) is zero if the i-th resource instate k supports capability j and is equal to one otherwise. An resourcemay support more than one capability. The operational continuityassumption implicitly constrains the space of feasible actions.

To reduce the computational effort needed to solve this problem, thesubject invention assumes that an enterprise has a tolerance orthreshold on the number of computer and software resources it is willingto change over a given decision period. This is to say that theenterprise is capacitated in some way. The resulting dynamic programmingproblem will be called the capacitated dynamic programming problem.Because of constraints on funding, man power and management complexity,an enterprise may want to limit the number of projects that it isundertaking over in given decision period.

At this point, the subject invention has now defined the constrainednumber of states and the constrained set of actions which are to beconsidered to achieve the maximum risk adjusted business value (RABV).These constrained sets of actions and life cycle states are provided asinputs to step 804.

Once these states and sets of actions are defined, the cumulative riskadjusted business value is calculated using the expression

$\begin{matrix}{J_{N}^{\overset{\_}{a}} = {{\sum\limits_{n = 1}^{N - 1}{\beta^{n - 1}Z_{n}}} + {\beta^{N}{\sum\limits_{j = 1}^{K}{{S_{j}\left( X_{N}^{j} \right)}.}}}}} & (1)\end{matrix}$This expression assumes that the planning horizon has N decision periodsand uses the constrained set of portfolio actions and life cycle statesacross the time horizon ā=(ā_(n)|0≦n≦N) where (X_(N) ^(j)) are theconstrained set of actions from step 803 and S_(j) are the constrainedlife cycles states from step 803 and Z_(n) is the risk adjusted businessvalue (RABV) at each decision period.

Once the states and related actions have been identified andconstrained, the maximum expected RABV is calculated for time N at step804. The objective of enterprise portfolio transition is to maximize theexpected total Discounted Risk adjusted business value

$\begin{matrix}{\max\limits_{\overset{\_}{a} \in \overset{\_}{A}}{{E\mspace{11mu}\left\lbrack J_{N}^{\overset{\_}{a}} \right\rbrack}.}} & (2)\end{matrix}$This relationship applies to the final set of actions and states at timeN. In order to identify the sets of actions and life cycle states foreach decision period that maximize the RABV, the functional recursiveequation is then:

$\begin{matrix}{\begin{matrix}{{f_{n}\left( \overset{\_}{x} \right)} = {\max\limits_{{\overset{\_}{a}}_{n} \in A}{E\left\{ {Z_{n} + {\beta\;{f_{n + 1}\left( \overset{\_}{x} \right)}}} \right\}}}} \\{= {\max\limits_{{\overset{\_}{a}}_{n} \in A}\left\{ {Z_{n} + {\beta\;{E\left\lbrack {f_{n + 1}\left( \overset{\_}{x} \right)} \right\rbrack}}} \right\}}} \\{= {\max\limits_{{\overset{\_}{a}}_{n} \in A}\left\{ {Z_{n} + {\beta{\sum\limits_{\overset{\_}{j} \in S}{p_{\overset{\_}{x}\overset{\_}{j}}^{\overset{\_}{a}}{f_{n + 1}\left( \overset{\_}{j} \right)}}}}} \right\}}} \\{= {\max\limits_{{\overset{\_}{a}}_{n} \in A}\left\{ {Z_{n} + {\beta{\sum\limits_{\overset{\_}{j} \in S}{{p_{x_{1}j_{1}}^{a_{n}^{1}} \cdot p_{x_{2}j_{2}}^{a_{n}^{2}}}\mspace{11mu}\cdots\mspace{11mu}{p_{x_{K}j_{K}}^{a_{n}^{K}} \cdot {f_{n + 1}\left( \overset{\_}{j} \right)}}}}}} \right\}}}\end{matrix}{{where}\text{:}}} & (3) \\{{f_{N}\left( \overset{\_}{x} \right)} = {\sum\limits_{j = 1}^{K}{S_{j}\left( x_{N}^{j} \right)}}} & (4)\end{matrix}$The backward induction technique is used to solve the recursive formula.Starting at n=N ƒ_(N)( x) is known for every state x. Next, ƒ_(N−1)( x)is computed for every state x using the fact that ƒ_(N)( x) which isknown. The optimal actions at N−1 are obtained and saved when ƒ_(N−1)(x) is computed at step 805. This recursive procedure is continued untiln=0 as tested in step 806. The quantity ƒ₀( x) represents the optimalRABV starting from initial state x. The set of actions and associatedlife cycle states that adhere to the maximum RABV are those states andsets of actions that are provided to step 807 where the transition datais formatted in the transition plan at step 807 and the optimizedtransition plan proceeds to step 714 of FIG. 7.

In essence, the subject invention develops the future TO BE requirementsin terms of all possible sets of actions and related life cycle states.The number of possible actions and life cycle states are constrained,that is reduced through the dynamic programming algorithms. Theseconstrained states and actions are used to calculate the RABV for eachdecision period. Finally, the subject invention, using a backwardinduction technique, selects the optimum states and sets of actions inorder to maximize the RABV across all the selected computer and softwareresources.

While the invention has been described for a preferred embodiment, thoseskilled in the art will recognize that the invention can be practicedwith modification within the spirit and scope of the appended claims.

1. A computer implemented method for generating a transition plan for anenterprise portfolio of computer resources, the computer performing thesteps of: storing in a computer memory an inventory data representingeach of a plurality of computer resources available to an enterprise,wherein said inventory data includes, for each of said computerresources, a baseline set of current computer resource capabilities,wherein each of said computer resources has an associated state datarepresenting its state within a life cycle state space including adevelop state, a steady state and a dead state; providing a set ofenterprise strategic goals for transitioning the enterprise portfolio ofcomputer resources; translating said enterprise strategic goals into aset of future computer resource requirements for at least one of saidcomputer resources; forming an initial transition plan, comprisingactions pertaining to at least one of said computer resources, fortransitioning from said current computer resource capabilities to saidfuture computer resource requirements, based on said current computerresource capabilities and said future computer resource requirements,wherein said actions include a retain action, a retire action and arestructure action, and wherein said actions transition the associatedstate data of said computer resource among states within said life cyclestate space; generating an optimized transition plan of actionspertaining to at least one of said computer resources for transitioningfrom said current computer resource capabilities to said future computerresource requirements, said generating including optimizing said initialtransition plan; and outputting the optimized transition plan, whereinsaid translating said enterprise strategic goals into one or more futurecomputer resource requirements is based on the expression{S_(j)(X^(i) _(n),a^(i) _(n))|0≦j≦K}  where n represents a specific timeperiod among said N time periods, S_(j) represents said future computerresource requirements, X^(i) _(n) represents the state, within said lifecycle state space, of an i-th resource in said enterprise portfolio ofcomputer resources at time n, a^(i) _(n) represents an action applied tosaid i-th resource at time n and, K represents a total number of saidcomputer resources, and wherein said optimizing said initial transitionplan includes selecting a sequence of actions based on maximizing abusiness value for said enterprise portfolio of computer resources,wherein said maximizing bases the business value of each computerresource on: the state of said computer resource within said life cyclestate space, a set of actions for transitioning said computer resourceamong states within said life cycle state space, and a reward for eachof said actions, wherein said reward is a cost associated with carryingout said action; wherein said optimizing initial transition planincludes a backward inductive maximization to maximize said businessvalue for said enterprise portfolio of computer resources based on thealgorithm:$J_{N}^{\overset{\_}{a}} = {{\sum\limits_{n = 1}^{N - 1}{\beta^{n - 1}Z_{n}}} + {\beta^{N}{\sum\limits_{j = 1}^{K}{S_{j}\left( X_{N}^{j} \right)}}}}$ā=(ā_(n))|0≦n≦N) where, ā represents a portfolio transition plan as aset of portfolio actions for the an entire time horizon, each portfolioaction being a set of actions, each action corresponding to at least onecomputer resource of said enterprise portfolio, J^(ā) _(N) represents acumulative adjusted business value, N represents a number of timeperiods considered for said transition plan, X^(j) _(N) represents aniterative state of a life cycle of an i-th resource in said enterpriseportfolio of computer resources, Z_(n) is a risk adjusted business valueat each decision period, and ā_(n) represents portfolio actions to beperformed at the n-th time period.
 2. A computer implemented system formanaging a portfolio of computer and software resources, said computersystem having software modules stored thereon and having a processoroperable to execute the software modules, the respective softwaremodules comprising computer instructions for: generating a transitionplan for an enterprise portfolio of computer resources, comprising:storing in a computer memory operatively connected to the processingsystem an inventory data representing each of a plurality of computerresources available to an enterprise, wherein said inventory dataincludes, for each of said computer resources, a baseline set of currentcomputer resource capabilities, wherein each of said computer resourceshas an associated state data representing its state within a life cyclestate space including a develop state, a steady state and a dead state;providing a set of enterprise strategic goals for transitioning theenterprise portfolio of computer resources; translating said enterprisestrategic goals into a set of future computer resource requirements forat least one of said computer resources; forming an initial transitionplan, comprising actions pertaining to at least one of said computerresources, for transitioning from said current computer resourcecapabilities to said future computer resource requirements, based onsaid current computer resource capabilities and said future computerresource requirements, wherein said actions include a retain action, aretire action and a restructure action, and wherein said actionstransition the associated state data of said computer resource amongstates within said life cycle state space; generating an optimizedtransition plan of actions pertaining to at least one of said computerresources for transitioning from said current computer resourcecapabilities to said future computer resource requirements, saidgenerating including optimizing said initial transition plan; andoutputting the optimized transition plan, wherein said translating saidenterprise strategic goals into one or more future computer resourcerequirements is based on the expression{S_(j)(X_(n) ^(i),a_(n) ^(i))|0≦j≦K} where n represents a specific timeperiod among said N time periods, S_(j) represents said future computerresource requirements, X_(n) ^(i) represents the state, within said lifecycle state space, of an i-th resource in said enterprise portfolio ofcomputer resources at time n, a_(n) ^(i) represents an action applied tosaid i-th resource at time n and, K represents a total number of saidcomputer resources, and wherein said optimizing said initial transitionplan includes selecting a sequence of actions based on maximizing abusiness value for said enterprise portfolio of computer resources,wherein said maximizing bases the business value of each computerresource on: the state of said computer resource within said life cyclestate space, a set of actions for transitioning said computer resourceamong states within said life cycle state space, and a reward for eachof said actions, wherein said reward is a cost associated with carryingout said action.
 3. A computer implemented system for managing aportfolio of computer and software resources, said computer systemhaving software modules stored thereon and having a processor operableto execute the software modules, the respective software modulescomprising computer instructions for: generating a transition plan foran enterprise portfolio of computer resources, comprising: storing in acomputer memory operatively connected to the processing system aninventory data representing each of a plurality of computer resourcesavailable to an enterprise, wherein said inventory data includes, foreach of said computer resources, a baseline set of current computerresource capabilities, wherein each of said computer resources has anassociated state data representing its state within a life cycle statespace including a develop state, a steady state and a dead state;providing a set of enterprise strategic goals for transitioning theenterprise portfolio of computer resources; translating said enterprisestrategic goals into a set of future computer resource requirements forat least one of said computer resources; forming an initial transitionplan, comprising actions pertaining to at least one of said computerresources, for transitioning from said current computer resourcecapabilities to said future computer resource requirements, based onsaid current computer resource capabilities and said future computerresource requirements, wherein said actions include a retain action, aretire action and a restructure action, and wherein said actionstransition the associated state data of said computer resource amongstates within said life cycle state space; generating an optimizedtransition plan of actions pertaining to at least one of said computerresources for transitioning from said current computer resourcecapabilities to said future computer resource requirements, saidgenerating including optimizing said initial transition plan; andoutputting the optimized transition plan, wherein said translating saidenterprise strategic goals into one or more future computer resourcerequirements is based on the expression{S_(j)(X_(n) ^(i),a_(n) ^(i))|0≦j≦K}  where n represents a specific timeperiod among said N time periods, S_(j) represents said future computerresource requirements, X_(n) ^(i) represents the state, within said lifecycle state space, of an i-th resource in said enterprise portfolio ofcomputer resources at time n, a_(n) ^(i) represents an action applied tosaid i-th resource at time n and, K represents a total number of saidcomputer resources, and wherein said optimizing said initial transitionplan includes selecting a sequence of actions based on maximizing abusiness value for said enterprise portfolio of computer resources,wherein said maximizing bases the business value of each computerresource on: the state of said computer resource within said life cyclestate space, a set of actions for transitioning said computer resourceamong states within said life cycle state space, and a reward for eachof said actions, wherein said reward is a cost associated with carryingout said action, wherein said instructions for optimizing initialtransition plan include instructions for a backward inductivemaximization to maximize said business value for said enterpriseportfolio of computer resources based on the algorithm:$J_{N}^{\overset{\_}{a}} = {{\sum\limits_{n = 1}^{N - 1}{\beta^{n - 1}Z_{n}}} + {\beta^{N}{\sum\limits_{j = 1}^{K}{S_{j}\left( X_{N}^{j} \right)}}}}$ā=(ā_(n)|0≦n≦N) where, ā represents a portfolio transition plan as a setof portfolio actions for the an entire time horizon, each portfolioaction being a set of actions, each action corresponding to at least onecomputer resource of said enterprise portfolio, J_(N) ^(ā) represents acumulative adjusted business value, N represents a number of timeperiods considered for said transition plan, X_(N) ^(j) represents aniterative state of a life cycle of an i-th resource in said enterpriseportfolio of computer resources, Z_(n) is a risk adjusted business valueat each decision period, and ā_(n) represents portfolio actions to beperformed at the n-th time period.